code: def testConv1d(self):
      graph = mtf.Graph()
      mesh = mtf.Mesh(graph, "my_mesh")
  
      filter_size = 3
      depth_dim = mtf.Dimension("depth", 2)
      length_dim = mtf.Dimension("length", 4)
      output_dim = mtf.Dimension("output", 2)
  
      x = tf.constant(
          [[1, 0], [0, 1], [1, 1], [2, 1]], dtype=tf.float32
      )
      mtf_x = mtf.import_tf_tensor(
          mesh, x, shape=mtf.Shape([length_dim, depth_dim])
      )
  
      initializer_mock = mock.MagicMock()
      initializer_mock.side_effect = initialize_by_shape(
          {
              (1, 3, 2, 2): [
                  [
                      [[1, -1], [0, 0]],
                      [[2, -2], [-1, 1]],
                      [[3, -3], [-2, 2]],
                  ]
              ],
          }
      )
  
      mtf_output = mtf.layers.conv1d(
          mtf_x,
          output_dim=output_dim,
          filter_size=filter_size,
          filter_initializer=initializer_mock,
      )
  
      mesh_impl = mtf.placement_mesh_impl.PlacementMeshImpl(
          shape=[], layout={}, devices=[""]
      )
      lowering = mtf.Lowering(graph, {mesh: mesh_impl})
      actual_output = lowering.export_to_tf_tensor(mtf_output)
  
      self.evaluate(tf.global_variables_initializer())
      self.evaluate(lowering.copy_masters_to_slices())
      actual = self.evaluate(actual_output)
  
      self.assertAllClose(actual, [[0, 0], [1, -1], [5, -5], [4, -4]])
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  import mesh_tensorflow
  from mesh_tensorflow import test_utils
  import mock
  import numpy
  import tensorflow.compat.v1
  import tensorflow_probability
  from tensorflow.python.framework import test_util
label_desc: Use image node_id 12 for calling the LayersTest obj's underlying member method code with example usage: obj.testConv1d() without return types